ROSES
Robust and Self-organizing Networks
| Coordinatore | TECHNISCHE UNIVERSITAT BERLIN
Organization address
address: STRASSE DES 17 JUNI 135 contact info |
| Nazionalità Coordinatore | Germany [DE] |
| Totale costo | 207˙628 € |
| EC contributo | 207˙628 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2009-IOF |
| Funding Scheme | MC-IOF |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-08-01 - 2012-07-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
TECHNISCHE UNIVERSITAT BERLIN
Organization address
address: STRASSE DES 17 JUNI 135 contact info |
DE (BERLIN) | coordinator | 207˙628.40 |
Mappa
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Obiettivo del progetto (Objective)
'Networks in transport, logistics, and telecommunication are pivotal for European and similar modern societies. The networks are complex and of very large scale. They must be operated both efficiently and reliable. At the intersection of mathematics, computer science, economics and engineering a huge body of linear and discrete network optimization methods has been developed. Methods for robust optimization form a younger field, topically attracting a lot of attention both mathematically and from practice. Recently, the concept of Recoverable Robustness, which we developed in an FET project, has significantly enlarged the possibilities to combine robustness and network optimization. The concept is well understood and proved useful in practice when the recovery is a linear program. The case when the recovery is an integer linear program has far broader modeling power. This case is almost untreated. In many applications the networks are not controlled by a central optimizing authority. They are operated by selfish players. A market mechanism must guarantee that the players in pursuit of their own benefit achieve global efficiency and reliability. Mechanism design is a thriving field with high international and interdisciplinary visibility. While many mechanisms for optimization problems are known, mechanisms that instill robust solutions are untreated. Given a market mechanism to instill robustness in a network controlled by selfish players at minimum loss in efficiency, a different application stands to reason: the networks created by credit obligations. To design regulations yielding robust credit networks it seems reasonable to complement classical, stochastic techniques with robust network optimization and algorithmic game theory. Such a new approach will have huge impact both scientifically and on financial stability. MIT’s ORC offers leading experts to cooperatively extend robustness to integer recovery, mechanism design and financial risk management.'
Introduzione (Teaser)
Modern society depends greatly on its transport, telecommunications and logistics networks. A wide range of methods exists for network optimisation, but one EU-supported project is helping to make these more robust and self-organising.